In [1]:
#Library loading
library(monocle3)
library(Seurat)
library(SeuratWrappers)
library(ggplot2)
library(dplyr)
library(patchwork)
library(magrittr)

#http://htmlpreview.github.io/?https://github.com/satijalab/seurat-wrappers/blob/master/docs/monocle3.html 참조
#https://satijalab.org/signac/articles/monocle.html
Loading required package: Biobase

Loading required package: BiocGenerics

Loading required package: parallel


Attaching package: ‘BiocGenerics’


The following objects are masked from ‘package:parallel’:

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB


The following objects are masked from ‘package:stats’:

    IQR, mad, sd, var, xtabs


The following objects are masked from ‘package:base’:

    anyDuplicated, append, as.data.frame, basename, cbind, colnames,
    dirname, do.call, duplicated, eval, evalq, Filter, Find, get, grep,
    grepl, intersect, is.unsorted, lapply, Map, mapply, match, mget,
    order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,
    rbind, Reduce, rownames, sapply, setdiff, sort, table, tapply,
    union, unique, unsplit, which.max, which.min


Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.


Loading required package: SingleCellExperiment

Loading required package: SummarizedExperiment

Loading required package: MatrixGenerics

Loading required package: matrixStats


Attaching package: ‘matrixStats’


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Attaching package: ‘MatrixGenerics’


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    colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
    colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
    colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
    colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
    colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
    colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
    colWeightedMeans, colWeightedMedians, colWeightedSds,
    colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
    rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
    rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
    rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
    rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
    rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
    rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
    rowWeightedSds, rowWeightedVars


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Loading required package: GenomicRanges

Loading required package: stats4

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Attaching package: ‘S4Vectors’


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Loading required package: IRanges

Loading required package: GenomeInfoDb


Attaching package: ‘monocle3’


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Attaching SeuratObject


Attaching package: ‘Seurat’


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In [7]:
#Plot size 조정
options(repr.plot.width = 8, repr.plot.height = 8, repr.plot.res = 600)
In [21]:
# Load the data from seurat rds
Epi.integrated <- readRDS('/home/minho2/Epi2_integrated.rds')
In [30]:
# Transfer seurat cluster info
list_cluster <-  Epi.integrated@meta.data[['seurat_clusters']]
names(list_cluster) <-  Epi.integrated@assays[["RNA"]]@data@Dimnames[[2]]
list_cluster
AAACCCAAGCAACCAG-1_1
0
AAACCCAAGGACTGGT-1_1
0
AAACCCACATCGCTGG-1_1
0
AAACCCAGTAGCGAGT-1_1
0
AAACCCAGTATGGGAC-1_1
1
AAACCCAGTCGTGGTC-1_1
4
AAACCCATCGTTCAGA-1_1
0
AAACCCATCTGGGAGA-1_1
5
AAACGAAAGAGAGGTA-1_1
4
AAACGAAAGCCAGACA-1_1
0
AAACGAAAGGTGCAGT-1_1
0
AAACGAAAGTAAGACT-1_1
2
AAACGAACAAAGCTCT-1_1
1
AAACGAACAAGGACAC-1_1
4
AAACGAACACTCATAG-1_1
0
AAACGAACAGCTCTGG-1_1
1
AAACGAACATTGAGGG-1_1
0
AAACGAAGTCTGTGAT-1_1
3
AAACGAAGTTGTACGT-1_1
4
AAACGAAGTTTGGCTA-1_1
0
AAACGAATCGACATAC-1_1
4
AAACGCTAGGGAGATA-1_1
0
AAACGCTCAACCGATT-1_1
2
AAACGCTCAAGCGAAC-1_1
2
AAACGCTCAGCAGTAG-1_1
1
AAACGCTCATCCGTGG-1_1
2
AAACGCTCATGGGCAA-1_1
0
AAACGCTGTGGCTTGC-1_1
2
AAACGCTTCAGCCTTC-1_1
0
AAAGAACAGAGTCACG-1_1
3
AAAGAACCATCGAGCC-1_1
2
AAAGAACCATGGGTCC-1_1
1
AAAGAACCATTGAAAG-1_1
4
AAAGAACGTAATCAAG-1_1
5
AAAGAACGTACTGAGG-1_1
0
AAAGAACGTGGTCTGC-1_1
1
AAAGAACTCCACAAGT-1_1
1
AAAGAACTCCACACCT-1_1
7
AAAGAACTCGGCTATA-1_1
5
AAAGAACTCTCCGAAA-1_1
1
AAAGAACTCTGACGCG-1_1
5
AAAGGATAGGCGCTCT-1_1
5
AAAGGATAGGGTATAT-1_1
1
AAAGGATAGTCCTGCG-1_1
0
AAAGGATCAGAGTTGG-1_1
1
AAAGGATCAGCGTGAA-1_1
5
AAAGGATCATCTCCCA-1_1
4
AAAGGATGTCTCGACG-1_1
2
AAAGGATGTGCTCTTC-1_1
4
AAAGGATTCGTTATCT-1_1
3
AAAGGGCCAATCTGCA-1_1
2
AAAGGGCCACGTATAC-1_1
0
AAAGGGCCATCCGGTG-1_1
3
AAAGGGCCATCTCCCA-1_1
0
AAAGGGCGTAACAAGT-1_1
4
AAAGGGCGTAGGCAAC-1_1
0
AAAGGGCGTGATTCAC-1_1
4
AAAGGGCGTGCTAGCC-1_1
4
AAAGGGCGTGTCGCTG-1_1
4
AAAGGGCTCCCAGGCA-1_1
1
AAAGGTAAGAATTGCA-1_1
0
AAAGGTAAGGTAGTAT-1_1
5
AAAGGTAAGTCCGCGT-1_1
0
AAAGGTACACATGTTG-1_1
2
AAAGGTACAGCAATTC-1_1
2
AAAGGTAGTACGATGG-1_1
0
AAAGGTAGTCTAATCG-1_1
0
AAAGGTAGTGTCTTGA-1_1
2
AAAGGTATCACTACGA-1_1
0
AAAGGTATCTGGGTCG-1_1
5
AAAGTCCAGATACAGT-1_1
1
AAAGTCCAGCGGCTCT-1_1
7
AAAGTCCCAGCTCTGG-1_1
4
AAAGTCCCATGGAATA-1_1
2
AAAGTCCGTAGACAGC-1_1
1
AAAGTCCGTCGCACGT-1_1
0
AAAGTCCGTCTGATCA-1_1
3
AAAGTCCGTGTCTTGA-1_1
5
AAAGTCCTCAGCCTTC-1_1
0
AAAGTCCTCGACGCTG-1_1
0
AAAGTGAAGAGCAAGA-1_1
2
AAAGTGAAGGGCTTCC-1_1
4
AAAGTGACAGGTTCCG-1_1
0
AAAGTGAGTTGCCATA-1_1
1
AAAGTGAGTTGCTCGG-1_1
1
AAAGTGATCGAACGGA-1_1
8
AAATGGAAGACGCCCT-1_1
2
AAATGGAAGAGCATCG-1_1
0
AAATGGACAAGTCATC-1_1
4
AAATGGACACCCTCTA-1_1
4
AAATGGACAGAGCTAG-1_1
3
AAATGGACAGCAAGAC-1_1
2
AAATGGAGTCAGTTTG-1_1
2
AAATGGATCTACCCAC-1_1
4
AACAAAGAGCTCTTCC-1_1
5
AACAAAGAGGTCGTGA-1_1
6
AACAAAGAGTACAACA-1_1
1
AACAAAGCACGTAGAG-1_1
3
AACAAAGGTGAGATAT-1_1
2
AACAAAGGTGTTAGCT-1_1
3
AACAAAGGTTTCGTAG-1_1
3
AACAAAGTCCCGAACG-1_1
6
AACAAAGTCGCGCCAA-1_1
0
AACAAAGTCTGCGATA-1_1
4
AACAACCAGATCGCCC-1_1
1
AACAACCAGGAGTCTG-1_1
3
AACAACCAGTCATTGC-1_1
0
AACAACCCAAATGAAC-1_1
1
AACAACCCACGGTAGA-1_1
0
AACAACCCAGTCAGTT-1_1
0
AACAACCGTTGAATCC-1_1
4
AACAACCTCATTCGGA-1_1
0
AACAAGAAGCGCACAA-1_1
2
AACAAGACACAGTCCG-1_1
2
AACAAGACAGAGTTCT-1_1
2
AACAAGAGTATCGCGC-1_1
5
AACAAGAGTCATCGGC-1_1
4
AACAAGAGTCGTCGGT-1_1
4
AACAAGAGTTCTCGTC-1_1
4
AACAAGATCCCAGGAC-1_1
1
AACAAGATCTCCTACG-1_1
1
AACAAGATCTCGTCAC-1_1
2
AACACACAGGATATGT-1_1
2
AACACACAGTAGGTTA-1_1
2
AACACACCACTGGATT-1_1
5
AACACACCATCCTATT-1_1
0
AACACACGTATGTCAC-1_1
1
AACACACGTCAGGTAG-1_1
1
AACACACTCAGATTGC-1_1
2
AACAGGGAGAAGCTGC-1_1
0
AACAGGGAGGCTCTCG-1_1
2
AACAGGGAGTGGTCAG-1_1
2
AACAGGGAGTTGTAAG-1_1
4
AACAGGGCAAGGTCAG-1_1
4
AACAGGGCATGCCGAC-1_1
0
AACAGGGGTACGCTTA-1_1
1
AACAGGGGTCACAATC-1_1
2
AACAGGGTCTCCGCAT-1_1
4
AACCAACAGTAGTCAA-1_1
0
AACCAACGTGTCTTCC-1_1
5
AACCAACTCACTTCTA-1_1
2
AACCAACTCAGCGCAC-1_1
6
AACCAACTCATAGGCT-1_1
4
AACCACAAGATTGCGG-1_1
4
AACCACAAGGGTCACA-1_1
0
AACCACACAGCGTGAA-1_1
5
AACCACAGTAGGCAGT-1_1
0
AACCACAGTATCTCTT-1_1
3
AACCACAGTCTCGGGT-1_1
2
AACCACATCAAGGAGC-1_1
0
AACCACATCAGACATC-1_1
2
AACCACATCGTAACCA-1_1
4
AACCATGAGATGCTGG-1_1
1
AACCATGAGGCTCCCA-1_1
0
AACCATGAGGTGAGCT-1_1
1
AACCATGGTGCCTGCA-1_1
4
AACCATGGTGGCTACC-1_1
1
AACCATGTCACTCTTA-1_1
0
AACCATGTCCGATCTC-1_1
0
AACCATGTCTTCTTCC-1_1
2
AACCCAAAGATGGGCT-1_1
3
AACCCAACAATTCTTC-1_1
4
AACCCAACACGAGGAT-1_1
0
AACCCAACACTTGACA-1_1
1
AACCCAACATGACCCG-1_1
1
AACCCAAGTACCGCGT-1_1
5
AACCCAAGTCGTGGAA-1_1
4
AACCCAAGTGGGTCAA-1_1
0
AACCCAATCACGGAGA-1_1
4
AACCCAATCGGCGATC-1_1
3
AACCCAATCGTGGGAA-1_1
1
AACCTGAAGAGATGCC-1_1
4
AACCTGACACCTGCTT-1_1
1
AACCTGACATCATCCC-1_1
4
AACCTGACATCCGCGA-1_1
0
AACCTGAGTCCTTGTC-1_1
0
AACCTGAGTCGCAGTC-1_1
2
AACCTGATCCGACAGC-1_1
2
AACCTGATCGAACACT-1_1
4
AACCTGATCGGAGCAA-1_1
2
AACCTGATCTAATTCC-1_1
4
AACCTTTAGTAAGAGG-1_1
1
AACCTTTCACGGTGTC-1_1
0
AACCTTTCATTGAGGG-1_1
4
AACCTTTGTATCACGT-1_1
0
AACCTTTTCCCGAACG-1_1
3
AACCTTTTCCCGTGTT-1_1
0
AACCTTTTCGCTTAAG-1_1
0
AACGAAACACAACGAG-1_1
0
AACGAAACACGCAAAG-1_1
3
AACGAAACAGTTAAAG-1_1
5
AACGAAAGTACTCCCT-1_1
3
AACGAAAGTGTTCGTA-1_1
1
AACGAAATCAGCATTG-1_1
4
AACGGGAAGCCTGCCA-1_1
6
AACGGGAAGCTGGCCT-1_1
1
AACGGGAAGTTCGCAT-1_1
3
AACGGGACACACACGC-1_1
4
AACGGGACACTGTGAT-1_1
3
AACGGGACATCTATCT-1_1
0
AACGGGAGTCTAACTG-1_1
⋯
AACGGGAGTTGGTGTT-1_1
5
AACGGGATCATAGCAC-1_1
4
AACGGGATCGTTAGAC-1_1
8
AACGGGATCTAGCCTC-1_1
1
AACGTCAAGAAGGTAG-1_1
3
AACGTCAAGACTAGAT-1_1
4
AACGTCAAGCGAGTAC-1_1
3
AACGTCACAATCTCGA-1_1
2
AACGTCACACCCAACG-1_1
4
AACGTCACACTGATTG-1_1
3
AACGTCACAGACGATG-1_1
1
AACGTCACATCAGTCA-1_1
0
AACGTCATCCATTGGA-1_1
4
AACTTCTAGAATTGTG-1_1
1
AACTTCTAGACAAGCC-1_1
3
AACTTCTAGATCGGTG-1_1
4
AACTTCTAGGTATAGT-1_1
3
AACTTCTAGTGCGACA-1_1
0
AACTTCTCACAATGCT-1_1
3
AACTTCTCATGGCACC-1_1
0
AACTTCTGTAGGGTAC-1_1
4
AACTTCTGTGCAGATG-1_1
6
AACTTCTGTTAAGGGC-1_1
1
AACTTCTTCATTACCT-1_1
1
AACTTCTTCCAAGAGG-1_1
5
AACTTCTTCTTCACAT-1_1
7
AAGAACACAGAGATTA-1_1
1
AAGAACACAGAGGACT-1_1
0
AAGAACAGTAGCTAAA-1_1
0
AAGAACAGTCTGATCA-1_1
6
AAGAACAGTTCTATCT-1_1
3
AAGAACATCGGACCAC-1_1
4
AAGAACATCTCTTCAA-1_1
3
AAGACAAAGAGGGTGG-1_1
2
AAGACAAAGCCGGATA-1_1
3
AAGACAACAAAGTATG-1_1
2
AAGACAACAACAAGTA-1_1
0
AAGACAACAAGTTTGC-1_1
4
AAGACAAGTAACCAGG-1_1
4
AAGACAAGTCAGCGTC-1_1
0
AAGACAAGTCTAGGCC-1_1
1
AAGACAAGTTATTCTC-1_1
3
AAGACAAGTTTACGAC-1_1
1
AAGACAATCACACGAT-1_1
2
AAGACAATCCCATAGA-1_1
2
AAGACAATCTTCGTAT-1_1
1
AAGACTCAGGGAGGGT-1_1
3
AAGACTCCAAATACGA-1_1
0
AAGACTCGTCGCTTAA-1_1
2
AAGACTCTCGAGTCCG-1_1
7
AAGATAGAGGCATCAG-1_1
1
AAGATAGCACCCTGAG-1_1
4
AAGATAGCAGGACTTT-1_1
4
AAGATAGGTCCATACA-1_1
1
AAGATAGGTGTAGCAG-1_1
3
AAGATAGGTTGACTAC-1_1
3
AAGATAGTCAAGAGTA-1_1
1
AAGATAGTCGACGAGA-1_1
4
AAGATAGTCGCACGAC-1_1
6
AAGATAGTCTAGTACG-1_1
1
AAGATAGTCTCTGCCA-1_1
2
AAGATAGTCTTCTGTA-1_1
2
AAGCATCAGGAACGCT-1_1
3
AAGCATCCAATTCGTG-1_1
0
AAGCATCCAGTAACAA-1_1
3
AAGCATCCATGCCGGT-1_1
0
AAGCATCGTAACCCGC-1_1
3
AAGCATCGTAGAGGAA-1_1
3
AAGCATCGTCGTGGTC-1_1
1
AAGCATCGTCTCACAA-1_1
2
AAGCCATAGCGGGTAT-1_1
1
AAGCCATAGTGATAAC-1_1
2
AAGCCATCAAACGTGG-1_1
4
AAGCCATCACGGGCTT-1_1
1
AAGCCATGTTCTATCT-1_1
5
AAGCCATTCCATCTCG-1_1
0
AAGCCATTCTGTCGTC-1_1
6
AAGCGAGAGTGAGGTC-1_1
5
AAGCGAGCAAGAGGTC-1_1
0
AAGCGAGGTCGTGATT-1_1
2
AAGCGAGGTGTTCATG-1_1
0
AAGCGAGTCCCGTTGT-1_1
3
AAGCGAGTCCCTTGTG-1_1
0
AAGCGAGTCTCTCGCA-1_1
0
AAGCGTTAGATTAGTG-1_1
1
AAGCGTTAGATTGACA-1_1
4
AAGCGTTAGATTTGCC-1_1
1
AAGCGTTAGGGAGGTG-1_1
1
AAGCGTTAGTAACGAT-1_1
2
AAGCGTTCAATCTAGC-1_1
0
AAGCGTTCACCAGCGT-1_1
5
AAGCGTTCAGGACTTT-1_1
1
AAGCGTTCATTAGGCT-1_1
5
AAGCGTTGTAGATTAG-1_1
0
AAGCGTTGTCGCTCGA-1_1
2
AAGCGTTGTGCAACGA-1_1
5
AAGCGTTGTTAAGTCC-1_1
0
AAGCGTTTCCTACACC-1_1
0
AAGGAATAGTAGTCTC-1_1
4
AAGGAATAGTATGACA-1_1
2
AAGGAATAGTCGGCAA-1_1
1
AAGGAATAGTGGCGAT-1_1
1
AAGGAATGTACCACGC-1_1
3
AAGGAATGTAGGGTAC-1_1
2
AAGGAATGTTCGGTCG-1_1
0
AAGGAATTCACTTTGT-1_1
1
AAGGAATTCGACCTAA-1_1
0
AAGGTAAAGCAAATGT-1_1
4
AAGGTAAAGGGTTAAT-1_1
0
AAGGTAAAGTCCGCCA-1_1
3
AAGGTAACAACGATTC-1_1
1
AAGGTAACATTGTACG-1_1
0
AAGGTAAGTGAATGAT-1_1
3
AAGGTAATCCTCTCTT-1_1
2
AAGTACCAGATTGACA-1_1
0
AAGTACCAGGAAGAAC-1_1
1
AAGTACCAGTGATGGC-1_1
3
AAGTACCCAAACGGCA-1_1
3
AAGTACCTCGCAGTTA-1_1
1
AAGTACCTCTCGTCGT-1_1
3
AAGTCGTAGAGCAGAA-1_1
2
AAGTCGTAGATAGCTA-1_1
0
AAGTCGTAGCATGATA-1_1
0
AAGTCGTAGCGGTATG-1_1
4
AAGTCGTAGGTTAAAC-1_1
3
AAGTCGTCACACACTA-1_1
3
AAGTCGTGTGGTAACG-1_1
0
AAGTGAAAGCGTGCTC-1_1
1
AAGTGAAAGTATGACA-1_1
0
AAGTGAAAGTTGTAAG-1_1
1
AAGTGAACAGTTAGGG-1_1
7
AAGTGAACATGCAGGA-1_1
0
AAGTGAAGTAATCAAG-1_1
2
AAGTGAAGTAGAGTTA-1_1
2
AAGTGAATCGATTTCT-1_1
0
AAGTTCGAGACTAAGT-1_1
2
AAGTTCGAGCACCTGC-1_1
1
AAGTTCGAGGCTGAAC-1_1
3
AAGTTCGCACACTTAG-1_1
5
AAGTTCGGTAACATAG-1_1
3
AAGTTCGGTACGTGAG-1_1
8
AAGTTCGGTATGGAGC-1_1
8
AAGTTCGGTGAGTAAT-1_1
2
AAGTTCGGTTAACAGA-1_1
4
AAGTTCGGTTGTGCCG-1_1
2
AAGTTCGGTTTCCAAG-1_1
2
AATAGAGCAGCTGTCG-1_1
3
AATAGAGGTAGAGATT-1_1
4
AATAGAGGTCGGTGTC-1_1
0
AATAGAGGTTCAGTAC-1_1
2
AATAGAGTCATAGAGA-1_1
0
AATCACGAGAGAGAAC-1_1
0
AATCACGCAGAACCGA-1_1
1
AATCACGGTCATTCCC-1_1
2
AATCGACAGACTCTTG-1_1
5
AATCGACAGATGCAGC-1_1
0
AATCGACGTAAGACCG-1_1
0
AATCGACGTACCTAAC-1_1
3
AATCGACGTCCAATCA-1_1
0
AATCGACGTGTTCAGT-1_1
1
AATCGACTCTGTGCTC-1_1
2
AATCGACTCTTCCCGA-1_1
5
AATCGTGAGACTACCT-1_1
2
AATCGTGAGGCCCGTT-1_1
2
AATCGTGAGTTACGAA-1_1
6
AATCGTGGTCATCCGG-1_1
2
AATCGTGGTTCAGCTA-1_1
6
AATCGTGTCCGATGTA-1_1
0
AATCGTGTCCTATGGA-1_1
3
AATCGTGTCTGCATAG-1_1
1
AATGAAGAGAAGGTAG-1_1
1
AATGAAGAGGCTGGAT-1_1
6
AATGAAGAGGGATCAC-1_1
3
AATGAAGCACATATGC-1_1
1
AATGAAGCATCGGATT-1_1
0
AATGAAGGTGCGGCTT-1_1
3
AATGAAGTCAGGAAGC-1_1
2
AATGAAGTCCGGTTCT-1_1
0
AATGAAGTCGGCCAAC-1_1
1
AATGAAGTCTTGTTAC-1_1
1
AATGACCCAGGAGACT-1_1
0
AATGACCTCTCCCATG-1_1
3
AATGACCTCTGGGAGA-1_1
0
AATGCCAAGGCGAAGG-1_1
3
AATGCCAGTAGAATGT-1_1
3
AATGCCAGTAGCTGTT-1_1
0
AATGCCAGTCCACTCT-1_1
3
AATGCCAGTCTACGAT-1_1
0
AATGCCATCATGCCGG-1_1
0
AATGCCATCCCGTTGT-1_1
5
AATGGAAAGAATGTTG-1_1
1
AATGGAAAGGTCATAA-1_1
3
AATGGAACAGACCTGC-1_1
3
AATGGAATCACAAGAA-1_1
0
AATGGAATCCATCTAT-1_1
3
AATGGAATCCTCAGAA-1_1
2
AATGGCTCAACGACTT-1_1
3
AATGGCTGTACGATGG-1_1
4
AATGGCTGTCCCGGTA-1_1
3
AATGGCTGTGGAACCA-1_1
2
Levels:
  1. '0'
  2. '1'
  3. '2'
  4. '3'
  5. '4'
  6. '5'
  7. '6'
  8. '7'
  9. '8'
  10. '9'
In [43]:
# Transfer seurat cluster info
cds <- as.cell_data_set(Epi.integrated)
cds <- cluster_cells(cds = cds, reduction_method = "UMAP")

cds@clusters@listData[["UMAP"]][["clusters"]] <- list_cluster
cds@clusters@listData[["UMAP"]][["louvain_res"]] <- "NA"
Warning message:
“Monocle 3 trajectories require cluster partitions, which Seurat does not calculate. Please run 'cluster_cells' on your cell_data_set object”
In [44]:
# Dimplot
p1 <- plot_cells(cds, show_trajectory_graph = FALSE)
p2 <- plot_cells(cds, color_cells_by = "partition", show_trajectory_graph = FALSE)
wrap_plots(p1, p2)
In [45]:
# Building trajectories with Monocle 3 it will take a long times
cds <- learn_graph(cds, use_partition = TRUE)
  |======================================================================| 100%
Warning message in min(data_df$weight[data_df$weight > 0]):
“no non-missing arguments to min; returning Inf”
In [48]:
# dimplot with monocle3 trajectory
plot_cells(cds, 
           label_groups_by_cluster = TRUE, 
           label_leaves = TRUE, 
           label_branch_points = TRUE,
           graph_label_size=1.5)
In [52]:
# Select starting point with gene name
max.avp <- which.max(unlist(FetchData(Epi.integrated, "Gzma")))
max.avp <- colnames(Epi.integrated)[max.avp]
cds <- order_cells(cds, root_cells = max.avp)
plot_cells(cds, color_cells_by = "pseudotime", 
           label_cell_groups = TRUE, 
           label_leaves = TRUE, 
           label_branch_points = TRUE)
Cells aren't colored in a way that allows them to be grouped.

In [61]:
plot_cells(cds, reduction_method= "UMAP")
In [59]:
cds
class: cell_data_set 
dim: 2000 19339 
metadata(1): citations
assays(2): logcounts counts
rownames(2000): Spp1 Hspb1 ... Tgm1 Cgnl1
rowData names(0):
colnames(19339): AAACCCAAGCAACCAG-1_1 AAACCCAAGGACTGGT-1_1 ...
  TTTGTTGTCTCTCTAA-1_2 TTTGTTGTCTTTGGAG-1_2
colData names(8): orig.ident nCount_RNA ... seurat_clusters ident
reducedDimNames(2): PCA UMAP
altExpNames(0):
In [ ]:

In [ ]: